nov verbal signals

Non-verbal behavior as courtship signals:

the role of control and choice in selecting partners

Karl Grammera,*, Kirsten Kruckb, Astrid Juettea, Bernhard Finka

aLudwig-Boltzmann Institut fuÈr Stadtethologie c/o Institut fuÈr Anthropologie, Althanstrasse 14,

Vienna A-1090, AustriabHumanethologisches Filmarchiv der Max-Planck Gesellschaft, Von-der-Tannstrasse 3-5,

Andechs D-82346, Germany

Received 10 December 1997

Abstract

In this work, we provide evidence based on direct observation of behavior in encounters of

opposite-sexed strangers, that women initiate and `̀ control'' the outcome. In the first minute of these

videotaped 10-min interactions, neither female `̀ solicitation'' behavior nor `̀ negative'' behavior is

strongly related to professed interest in the man, while female `̀ affirmative'' behavior at this stage

modulates male verbal output in later stages (4±10 min). Although the rate of female courtship-like

behavior is significantly higher in the first minute, it is only in the fourth to tenth minute that the rate of

female courtship-like behavior is correlated with professed female interest. We hypothesize that this

serves as a strategic dynamic reflecting sexual asymmetry in parental investment and the potential cost

of male deception to women. Ambiguous protean behavioral strategies veil individuals' intentions and

make their future actions unpredictable. These behavioral strategies may result in men's overestimation

of female sexual interest. D 2000 Elsevier Science Inc. All rights reserved.

Keywords: Mate selection; Initiation of sexual encounters; Courtship; Deception; Affirmative behavior;

Solicitation; Negative behavior; Interest; Protean behavior

According to many social non-evolutionary views, the sexes are identical in their behavior,

and if sex differences in behavior occur, they are a result of culture-specific learning

processes. These learning processes lead further to formation of gender stereotypes. In our

culture, socially constructed gender stereotypes allegedly require men to take the initiative in

* Corresponding author.

E-mail address: [email protected] (K. Grammer).

1090-5138/00/$ ± see front matter D 2000 Elsevier Science Inc. All rights reserved.

PII: S1 0 9 0 - 5 1 3 8 ( 0 0 ) 0 0 0 5 3 - 2

Evolution and Human Behavior 21 (2000) 371±390

initial mixed-sex encounters more often than women (Bruch, Giordano, & Pearl, 1986;

Garcia, Stinson, Ickes, & Bissonnette, 1991). If one follows the logic of McCormick and

Esser (1983), e.g., one finds that gender relations show an asymmetric distribution of

`̀ control behavior'' (i.e., who initiates and determines the outcome of opposite sex interac-

tions), which is almost completely norm-governed. According to this view, male-dominated

societies allow men to use power in order to obtain sex, whereas women are only allowed to

use power in order to avoid sex with unsuitable partners.

Evolutionists have developed hypotheses that can be used to derive predictions about

possible sex differences on the basis of asymmetric investment theory. Women having the

higher investment in their offspring (Trivers, 1972) have more to lose from making a poor

mate choice than men. Evolved female psychology is expected to include mechanisms that

could motivate active female choice and strategic control of interactions with male strangers,

thus leading towards the most favourable outcome for the female actors.

This does not imply that men are not cautious in mate selection and that they do not choose

actively or try to control female approaches. However, because of the asymmetric investment,

women should engage in control activities more often than men and should manipulate men

relatively more often and with greater subtlety than men would manipulate women. Thus, we

would expect a relative difference between male and female `̀ control'' behavior in friendly

encounters with strangers of the opposite sex.

1. Non-verbal signals in human courtship

In recent years, a repertoire of courtship signals has been established and empirically

validated (Grammer, 1990; Kendon & Ferber, 1973; Moore, 1985, 1995; Moore & Butler,

1989; Scheflen, 1965). Although these authors used different settings (single's bars,

laboratory, and client±therapist interactions), they all observed similarities in the repertoire

of female behaviors in the presence of male strangers, including `̀ come-on-effects'' of

these signals.

According to Moore's (1985) observations in single's bars, a woman is able to affect male

approaches by exhibiting or withholding non-verbal displays: `̀ they can elicit a high number

of male approaches allowing them to choose from a number of available men, or they may

direct solicitations at a particular man''. In this work, a courtship repertoire was established

from variation in the frequencies of different behaviors of women in single's bars vs.

cafeterias, and an index of this repertoire was positively correlated with male approaches in a

single's bar. Moore (1985) also showed that female interest could be assessed if a threshold

number of behaviors occurred out of a catalogue of 52 behaviors, but there was no direct

prediction of female interest in a man.

Furthermore, Grammer, Honda, Juette, and Schmitt (1999)1 showed that in the very

beginning (the first 120 s) of an interaction, traditional ethological behavior analysis was

1 This study used the first 2 min from the same experiments which are analyzed in this article. The study used

different observation categories and methods. The data in this study were analyzed by K. Kruck.

K. Grammer et al. / Evolution and Human Behavior 21 (2000) 371±390372

not able to reveal behaviors related to professed female or male interest in Japanese and

in German couples. In this analysis, it was only possible to show, with the help of digital

image processing of body movements, that qualitative changes in body movements could

predict professed female interest but only to a limited extent. These qualitative changes of

movement were detected in the speed, size and number of movements. The analysis also

showed that the changes were independent to the content of behavior. The analysis did

not assess possible effects of `̀ control'' behavior and its effects on subsequent behavior in

later stages of the encounter.

In the folk psychology literature on the use of signals in courtship, we find a striking sex

difference, which reflects the general relative difference in the mate selection psychology of

the two sexes. Women seem to be exquisitely familiar with what occurs during courtship.

They can describe in detail how they and other women flirt and pick up men. Even quite

successful men seem to have no idea what happens during flirtation (Perper & Fox, 1980). `̀ I

just know it works out'' was an answer often recorded by Kirkendall (1961) in his interviews

with young men. This might be a result of covert female control strategies.

Indeed, women are much better then men in encoding and decoding non-verbal behavioral

cues. From the earliest childhood, females exhibit more and more expressive, non-verbal

behavior than males do (e.g., facial expressions and touching; Argyle, 1988; Henley &

LaFrance, 1984). To quote DePaulo's (1992) review: `̀ Differences in ability, motivation, and

spontaneous expressiveness all converge to produce what may be one of the most pervasive

and important of all individual differences in the use of non-verbal behavior for self-

presentational purposes: Sex differences. . . [Women's] body movements are more involved

and more expressive'' (pp. 222±223). If this is the case, it seems reasonable to look for other

strategies and ways in which meaning is created in non-verbal exchanges. Grammer, Kruck,

and Magnusson (1998)2 found evidence of female manipulation of the man in a non-intrusive

and non-obvious way. If a woman is interested in a man, female rhythmic body movements

create `̀ hidden'' and highly complex patterns in synchrony with the male body movements.

The man perceives changes in her interest but is not able to ascertain their source. The

puzzling finding in this work was that female `̀ courtship signals'' were not predictive of the

particular pattern of behavior observed.

2. Control behavior, deception, and proteanism

In sum, the logic of this line of reasoning about asymmetric investment, women's need to

avoid male deception, and women's non-verbal skills, leads to the prediction that women are

expected to control men without the men recognizing the manipulation directly. We predict

that in an initial encounter, when the goals are unknown (and possibly conflicting), the

possibility of deception could play a major role in the interactions of both sexes. If female

parental investment and any cue of the possible adaptive loss resulting from bad decision

2 See above.

K. Grammer et al. / Evolution and Human Behavior 21 (2000) 371±390 373

making are higher for women than for men, then the possibility of male deception should play

a more important strategic role for women than for men.

Male deception about intentions or male quality may be the result of male±male

competition and female mate selection standards. The content of male advertisement is

controlled through female and male perception of an optimal mate. Indeed, men report that

they attempt to deceive women with status symbols (Buss, 1992), whereas women use

deception to enhance their physical appearance. Men also use deception more often when

they try to attain a short-term sexual relation. These low-investment copulations have been

cited more often among men than among women. Men test continuously for opportunities to

reduce investment and pursue women (Landolt, LalumieÂre, & Quinsey, 1995; Townsend,

Kline, & Wassermann, 1995). When comparing them against the background of male

deceptive mating tactics, women should have evolved psychological mechanisms that

motivate manipulation of men to reveal information about their intentions (what relationship

is he seeking if any Ð short or long term?). This evaluation should take place without male

awareness of female evaluation along this dimension (in which case male deceptive efforts

might be intensified). A consequence of this strategic female influence is that men should be

less aware of being manipulated for the purpose of revealing information about their mating

intentions and interests and, indeed believe that it was them, rather than the woman, who

initiated and guided the interaction.

Because of these conflicting demands Ð the utility of advertising and of deception Ð two

strangers who meet find themselves in a delicate situation. On the one hand, interest in the

other person has to be communicated in order to signal approachability, while on the other

hand, overt signalling could induce and raise the likelihood of deception. Yet, an `̀ overt''

approach might be dangerous for the woman in more respects. The approaching man could

start to insist on interacting with the woman after she has decided that the information from

the man did not suit her aspirations in mate selection; hence, this information can only be

transmitted verbally. The woman could run into the problem of getting rid of this man again,

or even worse, the man who received positive `̀ come ons'' could react aggressively to a

subsequent rejection.

The main challenge for communication in such a situation is that as soon as the man

perceives some female interest, his tendencies for deception might rise. The strategic solution

for the woman would be to influence the man to the extent of his not consciously processing

the come-on and thus believe that he himself initiated the approach.

Sabini and Silver (1982) postulated that the essence of initial opposite-sexed

encounters is the creation of ambiguity, where both sexes tend to hide their goals and

reveal information about possible commitment slowly. Such a situation entails the

`̀ communication paradox'' (Grammer, Fieder, & Filova, 1997) where intentions have

to be communicated without actually revealing these intentions. The effects of such

subliminal control strategies could lead to effects which have been described repeatedly

for male±female interactions. A number of studies have shown that men perceive

women in a more sexualized way than vice versa (Abbey, 1982; Abbey, Cozzarelli,

McLaughlin, & Harnish, 1987; Edmonson & Conger, 1985). In their terms, men usually

misconceive female friendliness and over-rate female sexual interest, whereas women

tend to underestimate male sexual interest. This research is usually done with ques-


tionnaires and rating scales or by interviewing subjects who have spent a certain time

together. Until today, detailed analyses of behavior of interactions of initial encounters

have not been provided.

The existence of such situations naturally leads to the development of `̀ mindreading'' with

individuals concealing their intentions and deceiving actively (Krebs & Dawkins, 1984).

Miller (1997) identifies three possible counter strategies against deception: (a) hiding of

intentions (poker face strategy); (b) tactical deception and misinformation (KGB strategy);

and (c) adaptive unpredictability (the protean strategy). The latter concept was developed by

Chance (1957) and elaborated by Humphries and Driver (1970) who called unpredictable

behavior `̀ protean'', after the Greek river god who eluded capture by continually, unpredic-

tably changing form. The adaptive logic of protean behavior lies in the fact that animals

generally evolve perceptual and cognitive capacities to entrain, track, and predict the

movement of other biologically relevant animals such as prey, predators, and potential

mates. Such predictive abilities mean that unpredictable behavior will often be favoured in

many natural pursuit±evasion predator±prey situations. Usually, hostile animals or con-

specifics capable of correct prediction punish predictability. Thus, endowing it with

characteristics that cannot be predicted by an opponent can enhance the effectiveness of

almost any behavioral tactic. As outlined above, human courtship is one situation where

deception and mindreading will play a role as outlined by Miller (1997) who expects a co-

evolutionary arms race in courtship between social prediction and social proteanism.

However, even if concealment of intentions and ambiguity through social proteanism are

created with respect to the goals of interactions, `̀ control'' strategies are necessary for

managing social interactions in one's favour. We would expect asymmetry in the use of

control strategies. The sex, which has the most to lose in an interaction with the other sex,

should try to control the interaction to a higher degree in order to get the information

necessary for decision making and minimization of costs.

In this view, men and women have different interests, which will find their expression in

how they act in encounters with the opposite sex. Questions of who, when, and how

interactions with a stranger of the opposite sex are initiated are thus central to any discussion

of intersexual interactions and their outcome.

We have studied encounters between strangers because they have numerous advantages.

These situations have a high degree of uncertainty. If one of the interactants develops interest

in his/her partner, it has to be communicated immediately because none of the interactants

knows how long the interaction will last. In such a situation with such a short window of

opportunity for courtship, the relevant information has to be conveyed very fast. This may

look like a limitation of our approach but `̀ waiting room situations'', where people randomly

meet strangers, are as natural as any other situation. This type of approach even has an

advantage; it offers a wide range of combinations of degree of interest among the participants

ranging from rejection to intense interest. If interest is then communicated, further courtship

may take place (Grammer, 1990).

Several hypotheses follow from our line of reasoning about behavioral interactions of

opposite sex persons who have not previously met.

(1) Women, when confronted with a male stranger, will try to `̀ control'' the man's

behavior more often than the reverse.


(2) Obvious courtship and `̀ come on'' signals will play a role only in the later stages of an

interaction when the woman has adequately assessed the man's intentions. In the very early

stages, women will show protean behavior, i.e., try to signal interest and disinterest erratically

in order to veil their intentions and avoid male tendencies for deception by `̀ blocking'' the

man's mindreading attempts.

(3) We also can assume that women will try to `̀ control'' men non-verbally, because non-

verbal behavior is, unlike verbal behavior, non-binding (Grammer, 1992). As the man's goals

are unknown to the woman, there is only one possibility when meeting a male stranger:

female solicitation should elicit male self-presentation.

(4) Under the pressure of male±male competition and an unknown time for interaction,

men will be forced to act in a direct and swift manner. Men should therefore use verbal self-

presentation in order to communicate interest in the woman.

3. Method

Male and female strangers (mean age 18.5 years, age range 18±23) were selected

randomly from different high school classes visiting the research institute where they met

in a `̀ hidden'' experiment. They were told that they would participate in a videorating

experiment. The experimenter left the room in order to `̀ answer the phone call'', thus leaving

the dyad alone. This situation is a non-artificial everyday waiting room situation. The

experimenter returned after 3 min. In this first 3 min, participants did not know how long they

would interact (phase I: data analysis limited to the first minute). Upon returning, the male or

female experimenter told the participants that the phone call would take another 10 min but

actual interruption took place at the tenth minute (phase II: 4±10 min). During the whole

time, they were videotaped through a one-way mirror. One pair of the originally 46

participants who suspected that they were being videotaped was excluded from the analysis

resulting in n = 45 pairs.

The interactions we used in this analysis are a subset of interactions, which have already

been analyzed with regard to laughter by Grammer (1990) with a different method and coding

system and with regard to the report by Grammer et al. (1998) within the conceptual

framework of interpersonal coordination. After the experiment, participants were debriefed

and asked for their consent. None of the participants refused consent. This is a widespread

method of obtaining comparable results on the interaction of two people called the `̀ dyadic

interaction paradigm'' by Ickes, Bissonnette, Garcia, and Stinson (1990).

For the analysis, we used three kinds of data.

1. Self-report. Self-report data included the results of a questionnaire assessment of the

subjective evaluation of the situation by the participants at the end of 10 min.

Participants rated the physical attractiveness of their partner [Likert scales: 1 (low)±6

(high)] and their level of interest in their partner [Likert scales: 1 (definitely not)±7

(definitely)] with the following statements: (1) I would give my telephone number to the

person present if I were asked for it, and (2) I would go out to the cinema with the

person if I were asked to. The rank Spearman correlation between these two items was


0.63 for women (n = 45, p < 0.01, Cronbach's alpha 0.80 for the two-item index), and

0.68 for men (n = 45, p < 0.01, Cronbach's alpha 0.83). Both items were combined into

one index of high and low professed interest in the partner as an independent variable

for the determination of non-verbal correlates of professed interest.

2. Non-verbal behavior. Analysis of non-verbal behavior consisted of a microanalysis

of the behavior of 45 pairs. The microanalysis of behavior was done on an Apple

Macintosh computer running MAC-MAX with a frame-by-frame interactive coding

program, developed by the authors. The ratio of time for collection of original

material to coding time effort was 1:110 resulting in 865 h of coding for the 45

dyads. Coding was completed for each of the 45 dyads and repeated for each of the

83 movement and speech categories. For the complete catalogue, see Grammer et al.

(1998). For the present analysis, only a subset of categories was used: `̀ courtship''

signals by women, and for partners, an index of `̀ negative'' (rejecting) signalling

and an index of `̀ affirmative'' behavior. Seventeen movements, which were defined

as being courtship signals, were those identified by Moore (1985), Givens (1978)

and others as flirtatious or courtship signals (see list of behavioral units, Table 2).

Signals of rejection or negative female signals have not previously been described in

the literature. There are basically two different strategies to indicate rejection: people

can avoid talking to each other, or use specific negative signals for rejection. To

define `̀ negative'' signals, we used an index (the simple sum of frequencies) of the

six behavioral units with the largest negative correlation with participants' professed

interest in the other person. Head nods defined `̀ affirmative'' behavior. Several

studies have shown that head nodding by the listener can positively reinforce a

speaker's verbal performance (for a review, see Argyle, 1988). This means that a

speaker who watches a person nodding will react by speaking more often and

longer. Male and female head nods were coded as `̀ affirmative'' behavior only if

they took place in parallel to the partner talking. Intercoder reliability for the non-

verbal behavior analysis was reported (Grammer et al., 1998) as 0.84 (percentage

agreement) for five recorded dyads.

3. Verbal performance. The duration of speech was used as a simplified measure of the

participants' verbal performance during the 10-min social interaction. Duration was the

sum of each onset and offset of speech for each member of the dyad.

4. Results

4.1. Subjective experience of the situation

The analysis of questionnaires showed that the development of self-reported male

interest in the woman depended on how attractive the man rated the woman. Professed

interest shows sufficient variation from a minimum of four for men (women: two) to a

maximum of 14 (women: 14). With such a range, we can analyze the episodes on a broad

spectrum from low interest to high interest. As predicted, professed male interest was

correlated with female attractiveness. The more attractive the man rated the woman, the


higher his professed interest (r = 0.37, n = 45, p = 0.004, two-tailed). Women did not

significantly link their interest in the man with male attractiveness (r = 0.23, n.s.).

Furthermore, the correlation did not differ significantly from those of the men when tested

with a method proposed by Sokal and Rohlf (1995). Interest in the partner showed an

interesting sexual asymmetry. Professed male interest in women was significantly higher

(n = 45, Mdn = 8.5 of 14 maximum) than professed female interest in men (Mdn = 6.5,

Wilcoxon; p = 0.0018; two-tailed). This shows that men, on average, were more

interested in women than the other way around, and it suggests that more women are

interesting for men than men are for women. This result corroborates the results found by

Abbey, McAuslan, and Ross (1998).

4.2. Non-verbal behavior: female courtship signals

In this part of the analysis, we attempted to determine the relationship between female

courtship signals and female-reported interest in her partner (Table 1).

Correlations of the behaviors were calculated first for the total duration of the

observation period (10 min, Table 1). Head akimbo is a behavioral pattern where the

hands are folded, the arms are moved up and the hands rest in a position behind the head

with the shoulders drawn back. This pattern is interpreted as `̀ look at my body''

Table 1

Female solicitation signals and professed interest in the male

Spearman correlation with professed female interest

Signal

Total

(10 min)

Phase I

(first min)

Phase II

(fourth± tenth min)

Author who

described signal

Head akimbo ÿ0.25 ÿ0.20 ÿ0.08 Goffmann (1979)

Primp 0.35* 0.18 0.31* Scheflen (1965)

Head toss ÿ0.17 ÿ0.09 ÿ0.13 Moore (1985)

Hair flip ÿ0.00 ÿ0.13 ÿ0.00 Moore (1985)

Head tilt 0.24 0.22 0.30* Moore (1985)

Breast presentation ÿ0.01 ÿ0.06 0.04 Moore (1985)

Palm 0.07 0.01 0.15 Moore (1985)

Head down 0.10 0.01 0.17 Ellis (1992)

Shrug 0.14 0.20 0.18 Givens (1978)

Coy smile 0.34* ± 0.34* Eibl-Eibesfeldt (1995)

Legs open 0.03 ÿ0.10 0.15 Grammer (1990)

Look through 0.31* 0.09 0.27 Moore (1985)

Short glance 0.51** 0.26 0.19 Moore (1985)

Illustrator 0.28 0.09 0.32* Moore (1985)

Arms flex ÿ0.21 ÿ0.16 ÿ0.13 Moore (1985)

Smile 0.13 0.20 0.13 Moore (1985)

Laugh 0.16 ÿ0.01 0.17 Moore (1985)

Total 0.45** 0.19 0.38**

* Significant at p < 0.05, two-tailed.

** Significant at p < 0.01, two-tailed.


(Goffmann, 1979), but for our participants, this pattern correlates negatively with

professed female interest. Primp refers to ordering one's clothes without a visible

necessity. In Head toss, the head moves down, followed by a fast circular upward move,

and then the head slowly returns to the original position. The Hair flip consists of the

same head movement as Head toss, the difference being that here, the hands are used to

throw the hair back. Neck presentation is a sideward Head tilt, supposedly signalling

submission or avoidance of the aggressive effect of the `̀ staring eyes'' when eye contact

occurs. In Breast presentation, both shoulders are moved back simultaneously. In Palm,

both palms are presented upwards. Head down lowers the head and gaze and is also

alleged to be a sign of submission in courtship. In Shrug, the shoulders are repeatedly

moved up and down. Coy smile is a smile followed immediately by a turning away and

lowering of the head. Legs open when sitting is self-explanatory. Look through was

defined as looking at the other person but not fixating on her or him and looking away

immediately; there is no pause between the movement of looking at the partner and

looking away from the partner. Short glance is directed at the partner for less than 3 s.

Illustrator is an illustrating hand movement when speaking. In Arms flex, one or both

arms are flexed at the elbow and held in front of the body. Smile is a contraction of the

Musculus zygomaticus major and Laugh is the same, but with the mouth open and sound

is produced.

Only a few patterns showed a significant positive correlation (Primp, Coy smile, Look

through, Short glance) with professed female interest (Table 1). This situation does not

change much when each of the behaviors was limited to either of the two phases. In order to

find out whether there were any changes in the correlations between the two phases, the

coefficients were z-transformed and tested with a paired t-test. Overall, there was a significant

increase in size of the correlation between phases I and II (t-test, df = 16, t = ÿ3.93, p =

0.001), with a higher correlation between professed interest and total solicitation score in

phase II (r = 0.38) than in phase I (r = 0.19). An index of solicitation behavior (the frequency

of solicitation behaviors) for the whole 10-min period was significantly positively correlated

(r = 0.45) with professed female interest in her partner.

4.3. Entropy and variability of courtship behavior

The frequency of courtship behavior decreased significantly from phase I to phase II.

Table 2 shows that most of the individual behaviors increased significantly in frequency

from phase I to phase II. This apparent contradiction is solved when we look at the

variability of courtship behavior. Variability is the quotient of the numbers of different

behaviors performed, divided by the number of all behaviors performed. A maximum

variability of 1 would mean that each behavioral act was different. In phase I, variability

was 0.39 and dropped in phase II to 0.13. This difference is highly significant (Wilcoxon

test, Z = ÿ5; p = 0.000, two-tailed). This variability could be an indicator of a higher

degree of proteanism in phase I.

In order to verify that proteanism could be reflected in variability, an analysis of entropy

was conducted. The basis of this analysis is information theory as outlined by Shannon and

Weaver (1949). Their approach was refined by Losey (1978) and applied to the analysis of


information content in behavior sequences by Hughes (1978). For this analysis, we developed

a computer program implementing the algorithms and source code provided by Press,

Teukolsky, Vetterling, and Flannery (1992).

A measure of uncertainty (U ) of events is defined as a monotonic increasing function of

the number of alternative behaviors available. U then is a logarithmic function of the number

of alternatives and it is the expectation of the function logPi (the probability of behavior i); it

is thus analogous to Shannon's measure of information and:

U � ÿXi

i�1

PilogPi:

Umax is the maximum uncertainty possible under a given repertoire. Thus, for a range of n

behaviors, Umax = log2n. In our case, this is 4.087. Hughes (1978) was able to show with this

method that behavior sequences in children's play show higher entropy and thus are more

freely variable than in exploration.

In our case, U was calculated for each participant and then the means from the first minute

and the last minute of the observation period were compared. The last minute was used

because the time range of observation has to be the same; thus, the expected probability of

occurrence for each behavior is the same. In the first minute, U = 1.50 and in the last minute,

U = 1.08. This difference was significant (t-test for pairs, df = 44, t = 4.93, p < 0.001). Hence,

Table 2

Frequencies of female courtship behavior (n = 45)

Mean of behaviors/minute (SEM)

Signal

Total

(10 min)

Phase I

(first min)

Phase II

(fourth± tenth min)

Wilcoxon test Z (p)

Phase I < Phase II

Head akimbo 1.04 (1.97) 0.26 (0.95) 0.61 (1.26) ÿ2.0 (0.04)

Primp 3.98 (3.36) 0.98 (1.47) 2.20 (2.50) ÿ2.8 (0.005)

Head toss 1.93 (3.77) 0.33 (0.73) 1.11 (2.80) ÿ2.3 (0.02)

Hair flip 3.15 (5.32) 0.54 (1.28) 2.04 (3.38) ÿ4.1 (0.0001)

Head tilt 12.87 (9.88) 1.93 (1.88) 8.09 (6.89) ÿ5.4 (0.0001)

Breast presentation 0.33 (0.63) 0.02 (0.15) 0.17 (0.38) ÿ2.0 (0.04)

Palm 0.28 (0.72) 0.04 (0.21) 0.22 (0.66) n.s.

Head down 60.41 (24.76) 7.26 (4.45) 40.96 (16.93) ÿ5.9 (0.0001)

Shrug 2.85 (7.58) 0.57 (1.26) 1.46 (4.51) n.s.

Coy smile 0.07 (0.33) 0.00 (0.00) 0.04 (0.21) n.s.

Legs open 2.26 (3.26) 0.46 (0.72) 1.35 (2.07) ÿ2.7 (0.007)

Look through 1.78 (2.39) 0.46 (0.86) 0.96 (1.66) n.s.

Short glance 60.98 (22.39) 0.67 (1.12) 4.37 (3.72) ÿ4.9 (0.0001)

Illustrator 6.52 (9.04) 0.57 (1.22) 5.00 (7.50) ÿ4.8 (0.0001)

Arms flex 6.70 (7.09) 0.93 (1.36) 4.22 (5.08) ÿ4.0 (0.0001)

Smile 10.15 (6.64) 1.41 (1.34) 6.33 (4.35) ÿ5.7 (0.0001)

Laugh 11.67 (6.80) 1.57 (1.36) 7.26 (4.81) ÿ5.6 (0.0001)

Total 18.7 (5.4) 18.0 (7.5) 14.3(4.8) Phase I > Phase II

1.8 (.05)


the uncertainty in the performance of behavior dropped significantly from the beginning of

the encounter to its end.

In the first minute (phase I) courtship behavior was more variable and not strongly

related to professed female interest in the initiation of the opposite-sexed encounters.

Yet, they seemed to become more strongly related in later stages (`̀ Total'' signal phase

II; Table 1).

This difference raises the question of how women with low professed interest use courtship

signals. In order to answer this question, the female participant's reports of interest in their

male partners were divided into three categories of professed interest. Three groups were

chosen because this yielded enough cases for each group. We then compared the low-interest

group to the high-interest group. In phase I, women with low professed interest sent 15.5

courtship signals per minute, whereas 19.1 came from highly interested women (Median test,

n.s.). The difference was statistically significant in phase II (11.4 for low interest vs. 15.5

courtship signals for high professed interest; Median test, exact probability p = 0.007). It

would appear that women with low professed interest cannot be discriminated on the basis of

their courtship behavior from those with high professed interest in phase I, but can be

discriminated by phase II.

4.4. Non-verbal behavior: negative signals

In order to determine a baseline of negative signalling, we calculated an index of the

six behavioral categories showing the lowest correlation with professed interest (negative

signalling; Table 3). Here, the results of our study contradict the literature on courtship

signals. The codes are self-explanatory with the exception of Deictograph. This is a

simple pointing movement with a stretched-out finger towards an object. Two of the

courtship signals, Head toss and Head akimbo, correlate negatively with professed

interest and are thus a part of the index for negative signals for women. Negative

signalling seems to be stable throughout both phases for women. It drops significantly

for men from phase I to phase II. For negative signalling, there is an interesting sex

difference in phase II. Women signal negatively more often in phase II than men do

(1.7 vs. 1.1: Wilcoxon test, p < 0.001, two-tailed). The overall frequencies of negative

signalling are astonishingly low when compared to courtship signals [see Total in Table

Table 3

Spearman rank correlations negative signals with professed interest (n = 45, both sexes)

Behavior Males Behavior Females

Roll sleeves up ÿ0.18 Head akimbo ÿ0.25

Look around ÿ0.19 Knees toward body ÿ0.18

Deictograph ÿ0.20 Move legs ÿ0.32*

Palm ÿ0.19 Cross legs ÿ0.31*

Close legs ÿ0.36* Arms parallel ÿ0.17

Smile ÿ0.20 Head toss ÿ0.17

Index ÿ0.40* ÿ0.22



Tab

le4

Mea

ns

of

beh

avio

rca

teg

ori

es(S

D)

and

Sp

earm

anra

nk

(r)

corr

elat

ion

sw

ith

pro

fess

edin

tere

stin

the

par

tner

(n=

45

,fo

rb

oth

sexes

)

Mal

esF

emal

es

To

tal

(10

min

)r

Ph

ase

I

(fir

stm

in)

r

Ph

ase

II

(fo

urt

h±

ten

thm

in)

r

To

tal

(10

min

)r

Ph

ase

I

(fir

stm

in)

r

Phas

eII

(fourt

h±

tenth

min

)r

Neg

ativ

e

sig

nal

s/m

in

1.5

8(0

.81

)ÿ0

.40

**

2.9

8a

(2.2

)ÿ0

.25

1.5

8(1

.0)ÿ0

.40

**

1.0

(0.9

3)ÿ0

.22

1.7

(2.0

)ÿ0

.19

1.1

0(1

.1)ÿ0

.16

Aff

irm

atio

n/

min

0.7

8(0

.8)

0.2

91

.26

a(1

.5)

0.1

20

.70

(0.8

1)

0.3

4*

0.8

5(0

.7)

0.2

41

.24

a(1

.2)

0.1

60.7

8(0

.73)

0.2

6

Spee

ch

du

rati

on

,

s/m

in

20

.7(8

.8)

0.3

3*

17

.92

b(8

.9)

0.1

12

1.1

(9.4

)0

.36

*2

1.3

(9.9

)0

.23

20

.2(1

1.8

)0.0

821.7

(10.4

)0.2

7

aP

has

eI>

Ph

ase

II,

Wil

cox

on

test

,p

<0

.05

.b

Ph

ase

I<

Ph

ase

II,

Wil

cox

on

test

,p

<0

.05

.

*S

pea

rman

ran

kco

rrel

atio

nw

ith

inte

rest

,p

<0

.05

.

**

Sp

earm

anra

nk

corr

elat

ion

wit

hin

tere

st,

p<

0.0

1.


2 (18.7) as compared to total negative signals in Table 4 (1.0)]: the ratio of negative to

positive signals (the number of negative signals divided by the number of positive

signals) is very low: it was 0.09 in phase I and dropped to 0.07 in phase II, a non-

significant change.

4.5. Affirmation and speech

The frequency of nodding was lower for both sexes in phase II than in phase I (Wilcoxon

test, p < 0.01, two-tailed, Table 4), and there was no significant sex difference. In contrast to

non-verbal behavior, the amount of male speech increased significantly from phase I to phase

II and only male speech duration correlated positively with male professed interest in phase

II. Female professed interest showed no significant relation to female affirmation behavior

and speech duration.

4.6. Female non-verbal control

Non-verbal control could be exerted by means of signals, which are not directly

linked to sexual signalling. One such signal is affirmation through nodding. This can

happen in every interaction independent of who is interacting. Furthermore, there might

be other behaviors, which are used in the same manner, but nodding is the only one

where we have a theoretical and experimental rationale for the assumed function of

nodding in the control of speech flow in social interactions. Affirmation through

nodding by a signal sender could lead to a rise in frequency of the receiver talking,

but there are several caveats. First, the signal sender cannot nod if the receiver is not

speaking. Then, it is not clear if the signal sender nods because the receiver is speaking

or the receiver is speaking because the signal sender nods. Even when we extend this

to nodding and speaking at different times of the interaction, there could be an

interaction between speaking at time 1 and speaking at time 2. The same is true for

nodding. Thus, the interactions between speaking and nodding at different times have to

be considered. In order to test this, we used the following approach as proposed by

Aiken and West (1996).

In the first model (Table 5, model A), male speech in phase II is the dependent

variable, while the independent variables were female nodding in phase I, male speech

in phase I and female nodding in phase II. Additionally, the three interactions among

the independent variables were entered into the regression equation.

The resulting regression model showed that affirmative behavior was significantly

affected by male speech in phase I, by female nodding in phase I, by the interaction

between male speech in phase I and female nodding in phase I, and by female nodding

in phases I and II. Model A shows that male speech duration in phases I and II were

significantly and positively associated. Furthermore, males spoke more in phase II in

relation to female nodding frequency in phase I. Female nodding and male speech in

phase I amplified each other and this interaction facilitated male speech in phase II.

High speech scores for men and the frequency of female nodding led to even higher

male speech scores in phase II.


Table 5

Results of backward multiple regression analysis (criterion for exclusion: probability of F-value � 0.050)

Model Trait Coefficient

Standard

coefficient t p

Affirmative behavior

Multiple R = 0.650, p = 0.000

A Male speech IIa

Male speech I ÿ3.783 0.594 4.556 0.000

Female nodding I 460.047 0.410 3.026 0.004

Male speech I � Female nodding I 1.657 0.320 2.279 0.028

Female nodding I � Female nodding II ÿ41.455 ÿ0.319 ÿ2.121 0.040

Multiple R = 0.694, p = 0.000

B Female nodding IIa

Female nodding I 2.137 0.595 5.259 0.000

Female negative behavior

Multiple R = 0.534, p = 0.001

C Male speech IIa

Male speech I 2.953 0.464 3.588 0.001

Multiple R = 0.528, p = 0.001

D Female negative behavior IIa

Male speech I 0.002 0.419 3.184 0.003

Male speech I � Male speech II 1.698 0.404 3.065 0.004

Female solicitation

Multiple R = 0.480, p = 0.001

E Male speech IIa

Male speech I 3.056 0.480 3.626 0.001

Multiple R = 0.283, p = 0.057

F Female solicitation IIa

Female solicitation I 0.182 0.283 1.958 0.057

Independent variables (predictors) are listed below. Only significant traits from the final regression

equations are reported.a Male speech in phase II Ð fourth to tenth minute Ð (male speech II), female nodding in phase II (female

nodding II), female negative behavior in phase II and female solicitation in phase II as dependent variables.

Model A: Predictors: (Constant), Male speech I, Female nodding I, Female nodding II, Male speech I±Female

nodding I, Female nodding I±Female nodding II, Male speech I±Female nodding II.

Model B: Predictors: (Constant), Male speech I, Male speech II, Female nodding I, Male speech I±Female

nodding I, Female nodding I±Male speech II, Male speech I±Female nodding I.

Model C: Predictors: (Constant), Male speech I, Female negative behavior I, Female negative behavior II, Male

speech I±Female negative behavior I, Female negative behavior I±Female negative behavior II, Male speech I±

Female negative behavior II.

Model D: Predictors: (Constant), Male speech I, Male speech II, Female negative behavior I, Male speech I±

Female negative behavior I, Female negative behavior I±Male speech II, Male speech I±Male speech II.

Model E: Predictors: (Constant), Male speech I, Female solicitation I, Female solicitation II, Male speech I±

Female solicitation I, Female solicitation I±Female solicitation II, Male speech I±Female solicitation II.

Model F: Predictors: (Constant), Male speech I, Male speech II, Female solicitation I, Male speech I±Female

solicitation I, Female solicitation I±Male speech II, Male speech I±Male speech II.


As is the case of male speech, female nodding in phases I and II amplified each

other and male speech score in phase II. This suggests the following interpretation. In

phase I, the male starts speaking, the female is likely to nod. This leads to higher

frequencies of male speech in phase II. Thus, female non-verbal behavior in phase I

controls male speech production in phase II.

In order to test whether male speech could determine female nodding and female nodding

determine male speech, we tested whether female nodding in phase II could be predicted by

male speech in phase I (Table 5, model B), but the only significant predictor for female

nodding in phase II was female nodding in phase I.

In order to assess the impact of female negative behavior, we made an analysis of

female negative behavior in phase I and male speech in phase II (Table 5, models C

and D). In this case, the interactions and female negative behavior in phase II and male

speech in phase I were entered into the model. Interestingly, it is only male speech in

phase I that had a significant effect on male speech in phase II. When we tested for the

reverse effect and female negative behavior in phase II, it was clear that this behavior

depended on male speech in phase I. In other words, the women reacted negatively if

the man spoke a lot. As we had predicted on the basis of protean theory, solicitation

behavior had no effect over time on male speech (Table 5, models E and F).

There remains the question of possible correlations between our criterion variables and

the problem of interpreting interaction effects between them. In order to address this issue,

we present a correlation matrix among the several criterion variables. Table 6 shows that

the dependent variables we used in the regression equations are somewhat correlated.

We have considered several ways for a possible solution (e.g., structure equation

modelling for a more causal interpretation of our argumentation) and finally decided to

use the presented multiple regression model to clear up the problem of having

seemingly independent tests of multiple correlated predictors. The analysis of our

observations shows that behavior remains rather constant during a particular time span.

Thus, we assumed that alternative methods, like causal modelling, did not meet the

needs of our argument, as these other models require greater independence between the

Table 6

Spearman rank correlations of dependent (criterion) variables in the final regression equations (n = 45)

Male

speech II Female nodding II

Female negative

behavior II

Female

solicitation

II

Male speech II ± 0.35* 0.25 0.29*

Female nodding II ± 0.19 0.35*

Female negative behavior II ± 0.52**

Female solicitation II ±

Male speech II = Male speech in phase II Ð fourth to tenth minute, Female nodding II = Female nodding in

phase II, Female negative behavior II = Female negative behavior in phase II, and Female solicitation II = Female

solicitation in phase II.



predictor variables than is the case. Furthermore, such an approach would generate

artifacts in the interpretation of interaction effects.

5. Discussion

Interactions between strangers, especially those between the two sexes, seem to be

governed by specific rules. Our results, like that of other researchers, suggest a general sex

difference in the professed interest in the other sex. Men are more interested in women than

the other way around. Women seem more reluctant than men to make contact. Our second

aim was to generate predictions from evolutionary-based meta-theories which predict

behavioral tendencies under a wide range of motivational factors.

The main methodological implication of this study is the utility of the concept of

proteanism in uncertain high-risk social situations. After performing many types of behaviors,

women seem to move to a more consistent repertoire at the end of the encounter.

Furthermore, women seem to exert more active control over male behavior: men produce

more verbal revelations than women, and the quantity of male self-presentation varies with

the female's behavior (predictions 1, 3, and 4, Section 2). This is suggested by the fact that

there was a clearer dependence of male behavior on the preceding female acts than vice versa.

We found that women solicited male verbal reactions actively and that female negative

behavior was influenced by male verbal behavior. In addition, female engagement in verbal

interaction did not necessarily signal interest.

Many theories assume that the sexes are essentially equal in their behavioral propensities

and that learning processes lead to social stereotypes that compel men to take the initiative in

initial mixed-sex encounters more often than women. We find that the women themselves

take control by sending subtle signals.

To our knowledge, this is the first time that these effects have been supported with

quantitative analyses of observational data. Our results support the hypotheses that sex

differences are present and that they follow the direction predicted by our evolution-

minded hypotheses: women try to elicit information from men and try to avoid the

possibility of deception.

When the situation is highly uncertain and time is limited, both sexes start signalling

immediately. There is no direct and strong initial relation between interest and signalling.

Interestingly, women use signals described in the literature as solicitation signals irrespective

of their professed interest.

Women with low and with high professed interest both send the same amount of

solicitation signals, but only highly interested women maintain the rate in phase II. This

view is underlined by the positive relation between female interest and an index of solicitation

in phase II (Prediction 2, Section 2). This interpretation is strengthened by the correlation

between affirmation and male speech duration. Female affirmation (Head nod ) seems to

amplify male speech production. This does not merely involve a simple feedback in which

affirmation triggers male speech production, which in turn causes female affirmation. Rather,

women appear to control male speech production through the use of non-verbal behavior.

This is consistent with our proposed strategy theory, which holds that women try to elicit


information from the man in order to make a decision. In the first stages of the contact,

women showed higher variability in their courtship behavior. This fact could be explained by

different reasons: either women behave in a protean way and send signals independent of

their interest, or women signal a complete repertoire and try to find out which behavior

modulates a man's response. In this view, every pair would develop its own non-verbal code

for courtship. However, this explanation is not sufficient to explain the fact that there was no

clear and distinct negative relation between solicitation behavior in the first stages and an

absence of professed interest. It would not be necessary to signal solicitation behavior, in

order to establish a common communicative repertoire, if no interest is present.

We predicted that women would tend to use covert strategies in order to avoid male

deception. At a first glance, this does not seem to be the case. Rather, decisions are made

quite early in an encounter as evidenced by a high correlation in behavior between the two

phases. Indeed, we know that first impressions are made very quickly and that those

impressions are generally quite accurate (Ambady & Rosenthal, 1992). Although decision

points can be very early, people still have to verify this first impression. This puts the signal

sender in a difficult situation: if the sender is interested but needs verification of information,

he/she has to be deceptive. In order to avoid detection in such a case, the signal sender (the

woman) should start signalling positively and try to veil her intentions. However, deceit

would select for efficient mindreaders who try to find more subtle cues, but we have

experimental evidence that men are not as skilled as women in deciphering non-verbal cues

(Argyle, 1988). It seems possible that men ignore female solicitation in early interactions.

Another male strategy would be to probe the signaller and demand evidence from additional

signals, but we currently have scarce evidence for such a strategy. The protean strategy would

also explain the fact that men continuously overestimate female sexual interest which seems

more likely than mindreading a protean woman.

An objection against a protean/deceptive explanation is the possibility that women might

test out men and then find out that the man is not interested and accordingly adjust their

professed interest to disinterest. If professed interest is the same as genuine interest, then

others present should be able to detect this.

Our results on solicitation behavior replicated Moore's (1985). Moore also found that an

index of only 10 out of 52 courtship behaviors could predict `̀ come on'' effects. Although

Moore did not make this point, such a finding of any 10 of 52 behaviors would result in 1.6 �1010 different signal combinations. In general, non-verbal signals are ambiguous and it could

be the quality of motor performance that denotes interest in such a situation as shown by

Grammer et al. (1999). Moreover, if the combinations of different signals have to be taken

into account by the observer, the complexity of the task becomes very challenging. On the

same data, with different analytic methods, Grammer (1990) showed that female interest can

be depicted from combinations of several signals performed simultaneously, i.e., laughter

combined with body posture. Thus, the general ambiguity of non-verbal signalling could lead

to the variability in female signalling. There are other possible explanations for the

deployment of solicitation signals by women, including emphasis on gender role identifica-

tion, and enhancement of their attractiveness to men. Women typically take longer than men

to evaluate man's acceptability. One possible interpretation of our results is that the women

were uncertain and thereby signalled conflicting cues. Shyness could be coupled with age.


Our participants (18.5 years) could be considerably younger than the participants from other

studies who where observed in bars and nightclubs.

Furthermore, cultural variations in the incidence and dynamics of solicitation behavior are

likely. Most of the researches cited in this paper were carried out in the United States or

Canada. Grammer et al. (1999) report the same repertoire for Japanese as Germans, but lower

rates of solicitation behavior with opposite-sexed strangers in Japan than in Germany.

There are also many known methodological problems in our study. The first problem is

sample size. The negative findings can be a result of our small sample size, because the

statistical power (the ability to detect true effects) for the analysis of our data was low. Other

speculations for the discrepancy between signalling solicitation and professed interest are that

the 10-min encounter with analysis based on 1 min was too short. Yet, the question remains as

to why there were more courtship signals in the very beginning than later stages in the 10-min

encounter. Also, the situation could be artificial, although this is not actually the case. A

waiting room situation is an everyday situation and interest in the other sex can occur in any

situation, so people should be familiar with this kind of encounter.

One of the surprising facts in this study was that women, if not interested, do not send clear

rejection signals. Thus, the man is likely to feel that he himself has started the interaction. In

fact, women show affirmation, engage in verbal exchange, and send sexually explicit signals

without having much interest in the man.

Female negative behavior is performed with astonishingly low frequencies. This can be

interpreted as a result of the woman's attempt to prod men to reveal information about

themselves. Negative signals were never strongly related to female interest at any time of the

interaction. Negative behavior was apparently a reaction to male speech production: men who

produced too much in phase I were highly likely to encounter female negative behavior later.

Possible goal incompatibility in encounters between complete strangers has great potential

for conflict for both sexes. Cultural norms could function to prevent people from signalling

negative emotions too directly and thereby reduce conflict. This argument is consistent with

our findings of low rates of female negative signals. The necessity for manipulation, and for

information, along with possible deception, leads to a highly ambiguous situation. Here men

might well perceive female behavior as an aggressive `̀ come on'', especially in light of

missing negative signals. In solving this dilemma, women attempt to create an ambiguous

situation by using non-verbal behavior, while simultaneously trying to control the man. As

soon as the highly discriminative woman determines that the man Ð who is under the

impression of being accepted Ð is not suitable, she does not clarify the situation. This

behavior can be interpreted as being `̀ aggressive'' in the sense that it manipulates men's

behavior and their social perceptions.

The results of this analysis show many inconsistencies, but also make clear that the

concept of proteanism in situations with high social risks might be useful in future

research. Further studies should entail ratings by third party participants on interest and

on the possible perception of interest. We would predict from protean theory that neither

men nor women should be able to predict female interest from the very early stages of

the encounters. Other directions for future research involve comparisons of the social

interactions in similar encounters in different contexts and with persons varying in age

and marital status.


Acknowledgments

Many thanks to Ivo Ponocny from the Institute of Psychology at the University of Vienna

for his valuable help with the statistical analysis in this paper.

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